This study involved preparation of Graphene oxide (GO) and reduced graphene oxide (RGO) using Hummer method and chemical method respectively. These carbon nanomaterials were used as starting material to make novel functionalize with thiocarbohydrazide (TCH) which was prepared by reacting CS2 with hydrazine to form GO or RGO- 4-amino,5-substituted 1H,1,2,4 Triazole 5(4H) thion (ASTT) ,(GOT) and( RGOT) respectively via cyclocondensation reaction. Also MnO2 nanorod was prepared to form hybridized with GOT and RGOT. A commercial multiwall carbon nanotube (MWCNT) and functionalization with carboxylic groups' (f-MWCNT) and its nanocomposite with GOT were also prepared. All carbon nanomaterials were characterized with different techniques such as Fourier transform infrared (FT-IR), X-ray diffraction (XRD), atomic force microscope (AFM) scanning electron microscope (SEM) and elemental analysis. XRD showed presence diffraction peak at 11.95 for GO and this diffraction disappeared for RGO. Diffraction peak of crystal planes for MnO2 matched well with standard data. The diameter of MnO2 nanotubes was determined using Debye scherrer equation and found to be 11.6nm corresponding with AFM image. The AFM images proves the growth of MnO2 nanotubes from the MnO2 nano spherical shape these images are very rare in the scientific literature. The real permittivity (ε'), imaginary permittivity (ε") and a.c conductivity (S.m-1) of all nanomaterials were measured by LCR meter at frequencies ranging from 100Hz to 100 KHz. The result showed the values of the real permittivity for RGO higher than GO at all frequencies while RGOTM have lower values of real permittivity at low frequency due to presence of MnO2 nanorods which affected the accumulation of charges. The imaginary permittivity of f-MWCNT-GOT and RGO were at low frequency higher than the real values due to their high conductivity. Also imaginary permittivity of f-MWCNT-GOT nanocomposites at all frequencies higher than real which have negative values at frequencies in range 400 to 4KHz .a.c conductivity for RGO and f-MWCNT-GOT nanocomposite have higher values compared with all prepared nanomaterial, at the same time the modified WE with f-MWCNT-GOT nanocomposite show the best detection limits in comparison with other prepared modified WE. Also the prepared nanomaterials were used to study novel sensing system and develop electrochemical sensor capable of detecting some of antibiotics such as Ampicillin (AMP), Amoxilline (AMOX) which have β-lactam ring and Tetracycline (TET) which contains four hydrocarbon rings using cyclic voltammetry (CV) technique via modification of the working electrode of the SPCE with the prepared nanomaterial by deposition process. f-MWCNT-GOT/SPCE nanocomposite showed higher electrochemical reaction response and lower limit of detection. The working electrodes surfaces were studied with AFM and SEM techniques. The value of apparent heterogeneous electron transfer rate constant (ks) was determined using the value of electron transfer coefficient (α) and the result showed that f-MWCNT-GOT/SPCE showed higher (ks).
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Leuconostoc bacteria was isolated from local pickled cabbage (Brassica oleracea capitata) and identified as Leuconostoc mesenteroides by morphology,biochemical and physiological. The local isolated L. mesenteroides bacteria under the optimal conditions of dextran production showed that, the highly production of dextran was 7.7g achieved by using a modified natural media comprised of 100ml whey, 10g refined sugar, 0.5g heated yeast extract, 0.01g CaCl2, 0.001g MgSO4, 0.001g MnCl2 and 0.001g NaCl at pH 6 and 25̊C for 24 hr of fermentation and by using 1ᵡ106 cell/ml as initial inoculums volume. Some applications in food technology (Ice cream, Loaf, Ketchup and Beef preservation) have been performed with processed dextran. The result
In this research, the size strain plot method was used to estimate the particle size and lattice strain of CaTiO3 nanoparticles. The SSP method was developed to calculate new variables, namely stress, and strain energy, and the results were crystallite size (44.7181794 nm) lattice strain (0.001211), This method has been modified to calculate new variables such as stress and its value (184.3046308X10-3Mpa) and strain energy and its value (1.115833287X10-6 KJm-3).
Thermal conductivity for epoxy composites filled with Al2O3 and Fe2O3 are
calculated, it found that increasing the weight ratio of Al2O3 and Fe2O3 lead to
increase in the values of thermal conductivity, but the epoxy composite filled with
Fe2O3, have values of thermal conductivity less than for epoxy composite filled with
Al2O3, for the same weight ratio. Also thermal conductivity calculated for epoxy
composites by contact to every two specimens (like sandwich) content same weight
ratio of alumina-oxide and ferrite-oxide, its found that the value of thermal
conductivity lays between the values of epoxy filled Al2O3 and of epoxy filled Fe2O3
Pulsed laser deposition (PLD) technique was applied to prepared Chromium oxide (Cr2O3) nanostructure doped with Titanium oxide (TiO2) thin films at different concentration ratios 3,5,7 and 9 wt % of TiO2. The effect of TiO2 dopant on the average size of crystallite of the synthesized nanostructures was examined by X-ray diffraction. The morphological properties were discussed using atomic force microscopy(AFM). Observed optical band gap value ranged from 2.68 eV to 2.55 eV by ultraviolet visible(UV-Vis.) absorption spectroscopy with longer wave length shifted in comparison with that of the bulk Cr2O3 ~3eV. This indicated that the synthesized samples a
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The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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